We design a regulation-triggered adaptive controller for robot manipulators to efficiently estimate unknown parameters and to achieve asymptotic stability in the presence of coupled uncertainties. Robot manipulators are widely used in telemanipulation systems where they are subject to model and environmental uncertainties. Using conventional control algorithms on such systems can cause not only poor control performance, but also expensive computational costs and catastrophic instabilities. Therefore, system uncertainties need to be estimated through designing a computationally efficient adaptive control law. We focus on robot manipulators as an example of a highly nonlinear system. As a case study, a 2-DOF manipulator subject to four parametric uncertainties is investigated. First, the dynamic equations of the manipulator are derived, and the corresponding regressor matrix is constructed for the unknown parameters. For a general nonlinear system, a theorem is presented to guarantee the asymptotic stability of the system and the convergence of parametersʼ estimations. Finally, simulation results are discussed for a two-link manipulator, and the performance of the proposed scheme is thoroughly evaluated.

中文翻译：

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使用批量最小二乘标识符的两链机器人的自适应控制

我们为机器人操纵器设计了一种规则触发的自适应控制器，以有效地估计未知参数，并在存在不确定性的情况下实现渐近稳定性。机器人操纵器广泛应用于模型和环境不确定性较高的远程操纵系统中。在此类系统上使用常规控制算法不仅会导致控制性能不佳，还会导致昂贵的计算成本和灾难性的不稳定性。因此，需要通过设计计算有效的自适应控制律来估计系统不确定性。我们将机器人机械手作为高度非线性系统的一个示例。作为案例研究，研究了具有四个参数不确定性的2-DOF机械手。首先，得出机械手的动力学方程，针对未知参数构造相应的回归矩阵。对于一般的非线性系统，提出了一个定理，以保证系统的渐近稳定性和参数估计的收敛性。最后，讨论了两连杆机械手的仿真结果，并对所提方案的性能进行了全面评估。